iBeacons and other radio frequency (RF)-based techniques are used to track visitors who visit stores and other venues. While these techniques are sufficient for coarse location determination, they generally fail to provide sufficient information about a visitor to identify the particular areas of a venue a user visits or the items or people with which the user interacted. For example, such techniques are generally not specific enough to identify that a user stopped to look at a particular item or portion of a shelf along an aisle of a store. Similarly, conventional techniques are not sufficiently granular to distinguish when a user at a conference communicates with another user (as opposed to simply being relatively nearby without interacting with the other user).
In addition to iBeacons and other RF-based tracking techniques, other conventional tracking techniques rely on a mobile device carried by a user (e.g., phones, tablets, wearables, etc.) to track the user. For example, a tracking system may rely on triangulation of Wi-Fi signals and/or global positioning system (GPS) signals associated with a user's mobile phone to track the user. Such techniques, however, require the user to carry a mobile device and generally rely upon the user cooperation and effort to load and use a particular application on the mobile device. In addition, these techniques also generally lack sufficient granularity to accurately identify the particular areas of a venue visited or the people or items with which the user interacted.
Additional techniques track users via video cameras, often combined with vision processing/facial recognition software. Such techniques, however, are often expensive to deploy and generally, like the previously discussed techniques, also do not provide sufficient information to accurately identify the particular areas of a venue visited or the people or items with which the user interacted.